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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Kai Sun,Zheng-Yu Yang,Pei Wang,Ying-Wu Chen.Mission Planning and Action Planning for Agile Earth-Observing Satellite with Genetic Algorithm[J].Journal of Harbin Institute Of Technology(New Series),2013,20(5):51-56.DOI:10.11916/j.issn.1005-9113.2013.05.010.
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Mission Planning and Action Planning for Agile Earth-Observing Satellite with Genetic Algorithm
Author NameAffiliation
Kai Sun College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China 
Zheng-Yu Yang College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China 
Pei Wang College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China 
Ying-Wu Chen College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China 
Abstract:
This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types (including multi-strip area, real time download request, and stereoscopic request) and complex satellite actions, such as observe action and data download action, are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process, the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.
Key words:  scheduling  mission planning  action planning  agile Earth-observing satellite  genetic algorithm
DOI:10.11916/j.issn.1005-9113.2013.05.010
Clc Number:S7
Fund:

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